Summary/Abstract Although influenza vaccination is the best available tool for reducing illnesses and deaths due to influenza, influenza vaccine effectiveness (VE) can vary substantially from year to year, depending on the antigenic match between circulating viruses and vaccine strains. To guide the ongoing development of influenza vaccination recommendations, we propose to conduct annual estimates of influenza VE, influenza burden of illness, and cases prevented by vaccination. We will conduct active surveillance for medically attended, laboratory-confirmed influenza in a predefined cohort. We will identify patients seeking ambulatory care for acute respiratory illness; eligible and consenting patients will be enrolled in the study. We will collect specimens for respiratory virus testing from all participants, which will be tested for influenza (including type, subtype, and lineage) via nucleic acid amplification. We will determine risk factors for influenza, and illness outcomes, through a combination of questionnaires and administrative healthcare databases. We will determine subjects' influenza vaccination history through self-report, validated using an immunization registry. Data will be shared with CDC and other participating sites to provide mid-season and end-of-season VE estimates. We will estimate VE using a test-negative design, comparing the odds of vaccination among subjects who test positive for influenza with the odds among subjects testing negative. We will provide annual estimates stratified by virus type/subtype/lineage and by age group. Because we are identifying patients with influenza from a defined cohort, we will also estimate the incidence of medically attended influenza in our study population, and estimate the number of influenza cases averted by vaccination. This project will also serve as a resource for studying VE and epidemiology of a novel influenza virus, should an influenza pandemic occur during the study period. We will work with CDC and other sites to prepare and pilot-test protocols for pandemic studies. In addition, this project provides a platform for respiratory syncytial virus (RSV) surveillance, which can provide important data on the epidemiology of RSV prior to licensure of RSV vaccines. We will test specimens for RSV and estimate the incidence of medically attended RSV in our study population. Finally, we will use data collected from this study to further explore potential biases and limitations of the test-negative design and to anticipate possible effects of RSV vaccine licensure on influenza VE estimates from test-negative studies. The proposed research will 1) generate data to guide influenza prevention actions and recommendations; 2) provide baseline data on RSV incidence prior to vaccine licensure; and 3) enhance our understanding of the test-negative study design.